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PyTorch Geometric (PyG) — graph neural network library built on PyTorch for learning on graphs and irregular structures. Provides message-passing layers (GCN, GAT, GraphSAGE, GIN, Transformer), mini-b
Use with AI
Install the MCP server or CLI to instantly fetch PyTorch Geometric documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/torch-geometric
docker pull biocontainers/torch-geometric:unknownProsit — deep learning framework for predicting MS2 fragment ion spectra and indexed retention times (iRT) from peptide sequences. Enables in silico spectral library generation for any organism and pr
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ProteinMPNN — deep learning-based protein sequence design from backbone structures. Uses message passing neural networks to predict amino acid sequences that fold into a given 3D backbone. Supports fi
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Use when working with PyG (PyTorch Geometric) — the PyTorch-based library for deep learning on graphs and irregular data structures. Supports graph neural networks (GNNs) including GCN, GAT, GraphSAGE
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AlphaPept — Python-based, open-source proteomics pipeline for DDA mass spectrometry data analysis. Provides feature detection, peptide identification via database search, deep learning-based scoring,
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Percolator — semi-supervised machine learning tool for rescoring peptide-spectrum matches (PSMs) from shotgun proteomics database searches. Uses target-decoy competition with SVM classification to sep
2 shared topics • 1 shared operation